Stephen D. Lee

28 papers receiving 1.1k citations

Peers

Stephen D. Lee
Comparison fields: 5 of 169
  • Pharmaceutical Science 106
  • Software 46
  • Cancer Research 103
  • Pharmacology 59
  • Biomaterials 80
Replace Shuhan Liu with:
Shuhan Liu China
Robert C. Wang United States
Jinying Chen China
Hans Schaefer Germany
Nikolay Borisov Russia
John Posner United Kingdom
Divya Sharma United States
Glenn A. Edwards Australia
Yihua Xu United States
Feifei Li China
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Countries citing papers authored by Stephen D. Lee

Since Specialization
Citations

This map shows the geographic impact of Stephen D. Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stephen D. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen D. Lee more than expected).

Fields of papers citing papers by Stephen D. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen D. Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stephen D. Lee. The network helps show where Stephen D. Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Stephen D. Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephen D. Lee Line = papers co-authored together Stephen D. Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007203
2 2019121
3
An Empirical Evaluation
1994116
4
Lipid excipients Peceol and Gelucire 44/14 decrease P-glycoprotein mediated efflux of rhodamine 123 partially due to modifying P-glycoprotein protein expression within Caco-2 cells.
2007112
5 2015111
6 201583
7 200767
8 199744
9 199135
10 201735
11 200633
12 197029
13 201423
14 201321
15 200719
16 201819
17 201215
18 201715
19 200810
20 20219

About Stephen D. Lee

Stephen D. Lee is a scholar working on Molecular Biology, Surgery, Oncology, Physiology and Immunology, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (5 papers), Cholesterol and Lipid Metabolism (5 papers), Adipose Tissue and Metabolism (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Cognitive Functions and Memory (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Atherosclerosis and Cardiovascular Diseases (2 papers) and Software Testing and Debugging Techniques (2 papers). The work is most often cited by research in Pharmaceutical Science (106 citations), Software (46 citations), Cancer Research (103 citations), Pharmacology (59 citations) and Biomaterials (80 citations). Stephen D. Lee has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Kishor M. Wasan, Kristina Sachs‐Barrable, A. Jefferson Offutt, Peter Tontonoz, Sheila J. Thornton, Dion R. Brocks, Ellen K. Wasan, F. Dénès, J. L. Shohet and Majid Sarmadi. Their work appears in journals such as Pharmaceutical Research, Molecular Pharmaceutics, Lipids in Health and Disease, The Journal of Experimental Medicine and Psychotherapy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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